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the perturbation method is applicable in any atmospheric model that allows for calculation of the relevant physical process information. The observational data used to evaluate the forecasts and the selected case studies in which the parameterization is tested will be introduced briefly as well as the analysis strategy for the suggested method. a. Physically based stochastic perturbations in the boundary layer We propose a concept of process-based model error representation in terms of a
the perturbation method is applicable in any atmospheric model that allows for calculation of the relevant physical process information. The observational data used to evaluate the forecasts and the selected case studies in which the parameterization is tested will be introduced briefly as well as the analysis strategy for the suggested method. a. Physically based stochastic perturbations in the boundary layer We propose a concept of process-based model error representation in terms of a
appropriate in the current context is the wave activity flux of Takaya and Nakamura (2001) . One particular feature of this formulation is its phase independence; this means that it discounts individual troughs and ridges and focuses on the dynamics of the entire wave packet instead ( Danielson et al. 2006 ). Focus on the entire wave packet is desirable, for instance, when studying model errors as opposed to initial condition errors ( Gray et al. 2014 ), and it would be interesting to find out whether
appropriate in the current context is the wave activity flux of Takaya and Nakamura (2001) . One particular feature of this formulation is its phase independence; this means that it discounts individual troughs and ridges and focuses on the dynamics of the entire wave packet instead ( Danielson et al. 2006 ). Focus on the entire wave packet is desirable, for instance, when studying model errors as opposed to initial condition errors ( Gray et al. 2014 ), and it would be interesting to find out whether
